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Last active August 15, 2019 19:09
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Benchmark for scaling GBDT
Raw
README.md

For reference here are the time it takes to run the following:

OMP_NUM_THREADS=$i python benchmarks/bench_hist_gradient_boosting_higgsboson.py \
    --n-leaf-nodes 255 --n-trees 100

lightgbm==2.2.1
xgboost==0.90
scikit-learn==0.21.2
Raw
benchmark_histogram_scaling.csv
threads time auc acc model
12 45.544142961502075 0.8273835213951107 0.7459995454545455 sklearn
12 48.39452910423279 0.8292525931837309 0.7476840909090909 sklearn
12 44.18983483314514 0.827102828104651 0.7458209090909091 sklearn
12 44.9314067363739 0.8276180921928156 0.7461645454545455 sklearn
12 44.64088273048401 0.8275933776606718 0.7463245454545454 sklearn
12 45.02442908287048 0.8276857616758038 0.7461613636363637 sklearn
12 44.33550572395325 0.8273367823457976 0.746075 sklearn
12 45.511662006378174 0.8269963899964421 0.7458945454545455 sklearn
12 46.0548255443573 0.8278266423414679 0.7463340909090909 sklearn
12 42.9952437877655 0.8272080847408102 0.7458827272727273 sklearn
10 46.35752034187317 0.8275720767144196 0.7461036363636364 sklearn
10 48.5894775390625 0.8277640340948885 0.7465013636363637 sklearn
10 46.52794694900513 0.8262696202308076 0.7454786363636363 sklearn
10 47.462074279785156 0.8276853747379538 0.7463463636363636 sklearn
10 46.87769913673401 0.8279120839283756 0.7464427272727273 sklearn
10 47.383312702178955 0.8283404468182936 0.7469222727272727 sklearn
10 45.57356309890747 0.827788979623499 0.7463931818181818 sklearn
10 45.856165647506714 0.8273459235176515 0.7459068181818181 sklearn
10 48.103076696395874 0.8285881510958534 0.7468963636363637 sklearn
10 45.88447165489197 0.8271602494621504 0.7459868181818182 sklearn
8 50.41839289665222 0.8277539823099679 0.74645 sklearn
8 50.92896318435669 0.827971579886893 0.7464686363636364 sklearn
8 50.0635941028595 0.8272407258439239 0.7459672727272727 sklearn
8 53.56699299812317 0.8288369242118229 0.7472568181818182 sklearn
8 48.28133034706116 0.8272210444911826 0.745945 sklearn
8 49.55193042755127 0.8270437857646844 0.7458277272727273 sklearn
8 49.8090181350708 0.8272367523061223 0.745940909090909 sklearn
8 52.89404916763306 0.8287548938397505 0.7470768181818181 sklearn
8 49.31590986251831 0.8273421777662474 0.7459836363636364 sklearn
8 51.37277579307556 0.8275453839841376 0.7462668181818182 sklearn
6 56.45400047302246 0.8273365120380007 0.7461413636363636 sklearn
6 57.379294872283936 0.8278308375420645 0.7465236363636364 sklearn
6 56.64788579940796 0.82776097462243 0.7462895454545454 sklearn
6 56.478214502334595 0.828427127506716 0.7469031818181818 sklearn
6 57.344210386276245 0.8278813590474843 0.7465795454545454 sklearn
6 58.78816199302673 0.8281945823253573 0.7467586363636364 sklearn
6 56.175089836120605 0.8274517356900087 0.746194090909091 sklearn
6 57.2385528087616 0.8278104003240236 0.7465245454545455 sklearn
6 54.62789726257324 0.8274151577139816 0.7459604545454546 sklearn
6 54.93461537361145 0.8274136565380432 0.7460818181818182 sklearn
4 64.36300325393677 0.8273337985177663 0.7459372727272727 sklearn
4 65.32503867149353 0.8276079281860894 0.7462263636363636 sklearn
4 65.26767706871033 0.8274457351647382 0.7460922727272727 sklearn
4 67.20011615753174 0.8277979932141506 0.746349090909091 sklearn
4 64.96915769577026 0.8274389859594997 0.7460172727272727 sklearn
4 66.72150611877441 0.8275631673705823 0.7462827272727273 sklearn
4 72.76017332077026 0.8292312841397246 0.74765 sklearn
4 65.45547294616699 0.8269119535309581 0.7457304545454545 sklearn
4 72.22659659385681 0.8292312841397246 0.74765 sklearn
4 67.50657916069031 0.8273595151188644 0.7461354545454545 sklearn
3 80.74829840660095 0.8274837951072965 0.7461981818181819 sklearn
3 79.91151094436646 0.8274837951114439 0.7461981818181819 sklearn
3 80.1730546951294 0.8274837951072965 0.7461981818181819 sklearn
3 80.06835389137268 0.8274837951072965 0.7461981818181819 sklearn
3 80.58833718299866 0.8273711117312829 0.7461740909090909 sklearn
3 80.90965867042542 0.8274837951072965 0.7461981818181819 sklearn
3 80.66904258728027 0.8274178099940444 0.7461872727272727 sklearn
3 80.64070987701416 0.8274837951072965 0.7461981818181819 sklearn
3 81.0389232635498 0.827575169946943 0.7462722727272727 sklearn
3 80.47553849220276 0.8274837951072965 0.7461981818181819 sklearn
2 114.45269823074341 0.8278144845980401 0.7463827272727273 sklearn
2 114.17699575424194 0.8278144845980401 0.7463827272727273 sklearn
2 113.44727730751038 0.8278144845980401 0.7463827272727273 sklearn
2 114.05001497268677 0.8278144845980401 0.7463827272727273 sklearn
2 114.02711725234985 0.8278144845980401 0.7463827272727273 sklearn
2 113.77791333198547 0.8278144845980401 0.7463827272727273 sklearn
2 113.97455739974976 0.8278144845980401 0.7463827272727273 sklearn
2 114.26400089263916 0.8278144845980401 0.7463827272727273 sklearn
2 113.2970449924469 0.8278144845980401 0.7463827272727273 sklearn
2 114.54056477546692 0.8278144845980401 0.7463827272727273 sklearn
1 197.22248601913452 0.8271696389988575 0.74592 sklearn
1 197.06517720222473 0.8271696389988575 0.74592 sklearn
1 196.82527327537537 0.8271696389988575 0.74592 sklearn
1 195.38466691970825 0.8271696389988575 0.74592 sklearn
1 195.26091194152832 0.8271696389988575 0.74592 sklearn
1 196.74993467330933 0.8271696389988575 0.74592 sklearn
1 196.67789816856384 0.8271696389988575 0.74592 sklearn
1 196.80709218978882 0.8271696389988575 0.74592 sklearn
1 196.71361565589905 0.8271696389988575 0.74592 sklearn
1 196.8555657863617 0.8271696389988575 0.74592 sklearn
12 44.85045766830444 0.8296208868862226 0.7476427272727273 lightgbm
12 42.740256786346436 0.8279943392985636 0.7462763636363636 lightgbm
12 41.75957131385803 0.8278959797971218 0.7462518181818182 lightgbm
12 40.61039113998413 0.8276891601565325 0.7461590909090909 lightgbm
12 42.862447023391724 0.8279943392985636 0.7462763636363636 lightgbm
12 41.92903184890747 0.8278959797971218 0.7462518181818182 lightgbm
12 40.438517570495605 0.8276891601565325 0.7461590909090909 lightgbm
12 40.57870268821716 0.8276891601565325 0.7461590909090909 lightgbm
12 42.84044885635376 0.8279943392985636 0.7462763636363636 lightgbm
12 40.42675065994263 0.8276891601565325 0.7461590909090909 lightgbm
10 41.69257378578186 0.8276891601565325 0.7461590909090909 lightgbm
10 41.50080490112305 0.8276891601565325 0.7461590909090909 lightgbm
10 41.32300400733948 0.8276891601565325 0.7461590909090909 lightgbm
10 41.59483075141907 0.8276891601565325 0.7461590909090909 lightgbm
10 42.75908803939819 0.8278959797971218 0.7462518181818182 lightgbm
10 41.747788429260254 0.8280550708694071 0.7464459090909091 lightgbm
10 41.505730867385864 0.8276891601565325 0.7461590909090909 lightgbm
10 42.96599841117859 0.8278959797971218 0.7462518181818182 lightgbm
10 43.90473985671997 0.8279943392985636 0.7462763636363636 lightgbm
10 41.63728332519531 0.8276891601565325 0.7461590909090909 lightgbm
8 49.289703130722046 0.8279943392985636 0.7462763636363636 lightgbm
8 51.34760928153992 0.8296208868862226 0.7476427272727273 lightgbm
8 48.0936279296875 0.8278959797971218 0.7462518181818182 lightgbm
8 51.23773908615112 0.8296208868862226 0.7476427272727273 lightgbm
8 48.09165167808533 0.8278959797962924 0.7462518181818182 lightgbm
8 49.19734263420105 0.8279943392985636 0.7462763636363636 lightgbm
8 49.12826752662659 0.8279943392985636 0.7462763636363636 lightgbm
8 46.84196710586548 0.8277210720449778 0.7460522727272727 lightgbm
8 49.02891969680786 0.8279943392985636 0.7462763636363636 lightgbm
8 49.023255825042725 0.8279943392985636 0.7462763636363636 lightgbm
6 56.204063415527344 0.8279943392985636 0.7462763636363636 lightgbm
6 53.310445070266724 0.8280550708694071 0.7464459090909091 lightgbm
6 56.56216216087341 0.8279943392985636 0.7462763636363636 lightgbm
6 54.96844792366028 0.8278959797971218 0.7462518181818182 lightgbm
6 52.38357472419739 0.8273779110169305 0.7458245454545455 lightgbm
6 55.03468346595764 0.8278959797962924 0.7462518181818182 lightgbm
6 52.70446062088013 0.8275275607538409 0.7459772727272728 lightgbm
6 52.4870285987854 0.8273779110169305 0.7458245454545455 lightgbm
6 52.81203484535217 0.8275275607538409 0.7459772727272728 lightgbm
6 52.62408638000488 0.8275145930027634 0.7459713636363636 lightgbm
4 63.75556659698486 0.8274509011020987 0.7458659090909091 lightgbm
4 64.29444313049316 0.8276881928554557 0.7461586363636363 lightgbm
4 64.63779211044312 0.8276881928554557 0.7461586363636363 lightgbm
4 64.75282096862793 0.8277475259041672 0.7460640909090909 lightgbm
4 64.77251315116882 0.8277220397371523 0.7460527272727273 lightgbm
4 63.402724266052246 0.8275275607538409 0.7459772727272728 lightgbm
4 66.48859524726868 0.8279244156849672 0.7462677272727273 lightgbm
4 66.2238998413086 0.8279244156849672 0.7462677272727273 lightgbm
4 64.7637357711792 0.8276881928554557 0.7461586363636363 lightgbm
4 64.44937324523926 0.8276881928554557 0.7461586363636363 lightgbm
3 81.32438206672668 0.8280550708694071 0.7464459090909091 lightgbm
3 81.21781063079834 0.8280550708694071 0.7464459090909091 lightgbm
3 80.98059701919556 0.8280550708694071 0.7464459090909091 lightgbm
3 80.21761059761047 0.8280550708694071 0.7464459090909091 lightgbm
3 80.93375778198242 0.8280550708694071 0.7464459090909091 lightgbm
3 80.85648322105408 0.8280550708694071 0.7464459090909091 lightgbm
3 80.93538236618042 0.8280550708694071 0.7464459090909091 lightgbm
3 81.2365345954895 0.8280550708694071 0.7464459090909091 lightgbm
3 81.136794090271 0.8280550708694071 0.7464459090909091 lightgbm
3 80.4391815662384 0.8280550708694071 0.7464459090909091 lightgbm
2 111.00352120399475 0.8274856769809409 0.7460081818181818 lightgbm
2 110.98957800865173 0.8274856769809409 0.7460081818181818 lightgbm
2 110.81591486930847 0.8274856769809409 0.7460081818181818 lightgbm
2 110.79300999641418 0.8274856769809409 0.7460081818181818 lightgbm
2 110.81765055656433 0.8274856769809409 0.7460081818181818 lightgbm
2 110.86973667144775 0.8274856769809409 0.7460081818181818 lightgbm
2 110.87486386299133 0.8274856769809409 0.7460081818181818 lightgbm
2 110.88273477554321 0.8274856769809409 0.7460081818181818 lightgbm
2 110.96099185943604 0.8274856769809409 0.7460081818181818 lightgbm
2 110.89613556861877 0.8274856769809409 0.7460081818181818 lightgbm
1 220.5628457069397 0.8289159065063556 0.7470381818181818 lightgbm
1 220.32190465927124 0.8289159065063556 0.7470381818181818 lightgbm
1 218.46198749542236 0.8289159065063556 0.7470381818181818 lightgbm
1 220.27575516700745 0.8289159065063556 0.7470381818181818 lightgbm
1 219.66240978240967 0.8289159065063556 0.7470381818181818 lightgbm
1 220.50205516815186 0.8289159065063556 0.7470381818181818 lightgbm
1 218.42210268974304 0.8289159065063556 0.7470381818181818 lightgbm
1 220.436527967453 0.8289159065063556 0.7470381818181818 lightgbm
1 220.24827408790588 0.8289159065063556 0.7470381818181818 lightgbm
1 218.576824426651 0.8289159065063556 0.7470381818181818 lightgbm
12 49.13096499443054 0.8302301905532321 0.7480727272727272 xgboost
12 48.40838074684143 0.8302301905532321 0.7480727272727272 xgboost
12 48.4840133190155 0.8302301905532321 0.7480727272727272 xgboost
12 48.85706305503845 0.8302301905532321 0.7480727272727272 xgboost
12 48.48190402984619 0.8302301905532321 0.7480727272727272 xgboost
12 48.292277574539185 0.8302301905532321 0.7480727272727272 xgboost
12 48.449721336364746 0.8302301905532321 0.7480727272727272 xgboost
12 48.427356243133545 0.8302301905532321 0.7480727272727272 xgboost
12 48.96416735649109 0.8302301905532321 0.7480727272727272 xgboost
12 48.30428600311279 0.8302301905532321 0.7480727272727272 xgboost
10 51.693400621414185 0.8302301905532321 0.7480727272727272 xgboost
10 51.961678981781006 0.8302301905532321 0.7480727272727272 xgboost
10 51.133633613586426 0.8302301905532321 0.7480727272727272 xgboost
10 51.967166900634766 0.8302301905532321 0.7480727272727272 xgboost
10 51.13858485221863 0.8302301905532321 0.7480727272727272 xgboost
10 52.104562759399414 0.8302301905532321 0.7480727272727272 xgboost
10 51.128451108932495 0.8302301905532321 0.7480727272727272 xgboost
10 52.146435499191284 0.8302301905532321 0.7480727272727272 xgboost
10 51.128002882003784 0.8302301905532321 0.7480727272727272 xgboost
10 51.874807357788086 0.8302301905532321 0.7480727272727272 xgboost
8 60.14023518562317 0.8302301905532321 0.7480727272727272 xgboost
8 58.53955626487732 0.8302301905532321 0.7480727272727272 xgboost
8 59.22322130203247 0.8302301905532321 0.7480727272727272 xgboost
8 58.727333545684814 0.8302301905532321 0.7480727272727272 xgboost
8 58.911420822143555 0.8302301905532321 0.7480727272727272 xgboost
8 58.36528134346008 0.8302301905532321 0.7480727272727272 xgboost
8 59.11362838745117 0.8302301905532321 0.7480727272727272 xgboost
8 58.248292207717896 0.8302301905532321 0.7480727272727272 xgboost
8 59.15737295150757 0.8302301905532321 0.7480727272727272 xgboost
8 58.48997712135315 0.8302301905532321 0.7480727272727272 xgboost
6 71.8937337398529 0.8302301905532321 0.7480727272727272 xgboost
6 68.94749188423157 0.8302301905532321 0.7480727272727272 xgboost
6 70.12714505195618 0.8302301905532321 0.7480727272727272 xgboost
6 70.4456582069397 0.8302301905532321 0.7480727272727272 xgboost
6 69.18525075912476 0.8302301905532321 0.7480727272727272 xgboost
6 71.00033044815063 0.8302301905532321 0.7480727272727272 xgboost
6 70.57736730575562 0.8302301905532321 0.7480727272727272 xgboost
6 69.85490441322327 0.8302301905532321 0.7480727272727272 xgboost
6 69.6651930809021 0.8302301905532321 0.7480727272727272 xgboost
6 71.89432287216187 0.8302301905532321 0.7480727272727272 xgboost
4 90.74173092842102 0.8302301905532321 0.7480727272727272 xgboost
4 90.187016248703 0.8302301905532321 0.7480727272727272 xgboost
4 90.68139362335205 0.8302301905532321 0.7480727272727272 xgboost
4 89.4472644329071 0.8302301905532321 0.7480727272727272 xgboost
4 90.98931860923767 0.8302301905532321 0.7480727272727272 xgboost
4 89.85527801513672 0.8302301905532321 0.7480727272727272 xgboost
4 89.66032433509827 0.8302301905532321 0.7480727272727272 xgboost
4 89.18982076644897 0.8302301905532321 0.7480727272727272 xgboost
4 89.68556261062622 0.8302301905532321 0.7480727272727272 xgboost
4 89.82674646377563 0.8302301905532321 0.7480727272727272 xgboost
3 107.64946150779724 0.8302301905532321 0.7480727272727272 xgboost
3 112.598801612854 0.8302301905532321 0.7480727272727272 xgboost
3 112.11399602890015 0.8302301905532321 0.7480727272727272 xgboost
3 112.65123558044434 0.8302301905532321 0.7480727272727272 xgboost
3 105.72045993804932 0.8302301905532321 0.7480727272727272 xgboost
3 105.3522961139679 0.8302301905532321 0.7480727272727272 xgboost
3 112.17547345161438 0.8302301905532321 0.7480727272727272 xgboost
3 105.34462571144104 0.8302301905532321 0.7480727272727272 xgboost
3 105.75883626937866 0.8302301905532321 0.7480727272727272 xgboost
3 106.44140338897705 0.8302301905532321 0.7480727272727272 xgboost
2 150.44044947624207 0.8302301905532321 0.7480727272727272 xgboost
2 132.0142467021942 0.8302301905532321 0.7480727272727272 xgboost
2 133.06347918510437 0.8302301905532321 0.7480727272727272 xgboost
2 146.8867666721344 0.8302301905532321 0.7480727272727272 xgboost
2 148.33905267715454 0.8302301905532321 0.7480727272727272 xgboost
2 131.29206895828247 0.8302301905532321 0.7480727272727272 xgboost
2 132.6037220954895 0.8302301905532321 0.7480727272727272 xgboost
2 147.20597076416016 0.8302301905532321 0.7480727272727272 xgboost
2 132.8200695514679 0.8302301905532321 0.7480727272727272 xgboost
2 149.4499397277832 0.8302301905532321 0.7480727272727272 xgboost
1 245.21178793907166 0.8302301905532321 0.7480727272727272 xgboost
1 242.34380459785461 0.8302301905532321 0.7480727272727272 xgboost
1 244.96775698661804 0.8302301905532321 0.7480727272727272 xgboost
1 242.71097946166992 0.8302301905532321 0.7480727272727272 xgboost
1 242.12387371063232 0.8302301905532321 0.7480727272727272 xgboost
1 244.79304695129395 0.8302301905532321 0.7480727272727272 xgboost
1 242.54142713546753 0.8302301905532321 0.7480727272727272 xgboost
1 244.73015117645264 0.8302301905532321 0.7480727272727272 xgboost
1 244.57835245132446 0.8302301905532321 0.7480727272727272 xgboost
1 243.49794363975525 0.8302301905532321 0.7480727272727272 xgboost
Raw
xgboost_benchmark_histogram_scaling.csv
threads time auc acc model
12 36.72745895385742 0.8302326297738187 0.7480718181818182 xgboost
12 36.430359840393066 0.8302326297738187 0.7480718181818182 xgboost
12 36.68353772163391 0.8302326297738187 0.7480718181818182 xgboost
12 36.61000633239746 0.8302326297738187 0.7480718181818182 xgboost
12 36.453571796417236 0.8302326297738187 0.7480718181818182 xgboost
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